Dynamic interactions of very large neuronal population in the brain underlie our ability to generate expectations about the outcome of a future event, learn the complex laws of nature and create art. These dynamic interactions are also responsible for relatively lower-level functions, such as motor control and respiratory control, in both humans and animals. Sensory perception and higher cortical functions emerge from these intricate dynamic interactions in very large cortical network. Therefore, understanding the functioning of a cortical area requires following the dynamics of a neuronal population activity with high spatial and temporal resolution.
The basic neural research in sensing neural activity in (preferably free-behaving) animal models allows for better understanding of brain functionality. This basic research has led to continuous development of many experimental techniques where theories of brain functions can be examined in real-time by tracking neuro-physiological signals. These studies are worth pursuing not only due to their scientific merit but since they provide the foundations essential for tracking and treating in early stages of diseases. For example, motor disorders in Parkinson's disease or vision and hearing dysfunction after accidents or brain damage events may be tracked or treated using these studies. These studies are also vital to finding new ways to restore functionality for paralyzed patients.
Previously available techniques for brain interrogation include, among others, functional MRI (fMRI) and positron emission tomography (PET), as well as near-infrared spectroscopy. These techniques rely on the metabolic consequences of changes in neuronal activity and can obtain spatial resolution (below 100 microns in some cases). These methods typically monitor regional changes in cerebral blood flow and blood oxygenation level, relying on the coupling between local electrical activity and the cerebral microcirculation. However, these techniques are slow relative to the neuronal activity, which limits the ability to track neuronal signals.
Other conventional recording techniques for brain activity provide temporal resolution in the millisecond range but these techniques have undue limitations in spatial resolution. For example, electroencephalography (EEG) non-invasively records electrical signal from an average activity of the brain through the skull and reflects the massed activity of many neurons, thus leading to a limited use. While signal quality can be improved with more invasive recording where similar electrodes are placed on the dura (a protective layer of tissue covering the brain) or on the cortical surfaces of the brain, resolution is still somewhat limited.
Another approach for brain activity monitoring involves inserting an electrode (or array of electrodes) into the cerebral cortex and recording spikes and local field potentials from the cortex area. Recent advances in micro-fabrication technologies allowed for a realization of dense arrays as high as 128×128 elements that are implanted in the cortex. This electrode approach facilitates brain activity monitoring and can provide valuable information on brain activity, sensory perception and higher cortical functions. Such an electrode array has been examined as part of a “brain-machine interface” (BMI) approach to allow movement control for paralyzed patients. However, multiple neuron recordings provide a significantly more challenging decoding problem than EEG signals, both because the signal is complex and because the processing demands are large. Electrical signals obtained using this type of approach are typically digitized at high rates (typically above 20 kHz) for many channels. In addition, the signals typically need to be separated from the noise and decoding algorithms typically are needed to process neural activity into some pattern or provide useful control command signals within a meaningful time frame (e.g., on the order of 200 milliseconds). Furthermore, this invasive electrode approach involves a neurosurgical operation to install the electrodes, and the electrode lifetime is limited because the immune system slowly walls off and even rejects the electrodes.
One method of brain imaging known as Intrinsic Optical Signal (IOS) imaging is used for mapping activity patterns of the cerebral cortex. It has provided the bulk of the known functional information about the columnar architecture, one of the key features of sensory and motor cortex organization. IOS imaging is typically invasive, requiring at least an incision in the scalp and often craniotomy, but measures activity patterns with spatial resolutions below 0.1 mm. While the bulk of IOS imaging work has involved craniotomy procedures, the use of far red and NIR light allows high-resolution IOS results to be obtained through skull and intact meninges. IOS imaging is based on imaging photons reflected diffusely from a surface of live brain tissue illuminated by an external light source. This diffuse reflection is a consequence of single and multiple scattering of photons within the turbid, but only weakly absorbing, tissue of the cerebral cortex. The signals discerned by imaging this diffuse reflection are called “intrinsic” because no exogenous stains or indicator dyes are used. Fortuitously, the light scattering and absorption processes that govern the diffuse reflection vary with neural activity and thus provide useful functional information. Activity-dependent changes in diffuse reflectance have several different physical origins, including changes in the amount of hemoglobin with brain volume elements, changes in the oxygenation state of hemoglobin, and light scattering changes that are independent of hemoglobin. To date, IOS imaging systems have been implemented as bulky, fixed instruments, requiring that the subject be immobilized and, almost always anesthetized.
The above-mentioned difficulties have presented challenges to sensing and analyzing biological characteristics.